ABSTRACT: Cancer of the small intestine (SI) is rare and typically presents as Gastrointestinal Neuroendocrine Tumors (SI-NETs). Seminal studies demonstrate that colorectal tumors arise when a complement of transformative mutations occur in colonic stem cells. In contrast, little is known about the cellular origin and underlying biology of SI-NETs. SI-NETs feature an overabundance of hormone-secreting neuroendocrine cells, and are typically undetectable until metastatic tumors cause carcinoid syndrome. Owing to their slow proliferation rate, unknown genetic etiology, and lack of cell culture models that accurately represent disease phenotypes, SI-NETs are technically challenging to study in vivo and represent an understudied cancer that is on the rise. Knowledge gaps in the understanding of oncogenic transformation driving SI-NET initiation, as well as the basic cellular composition of human SI-NETs, have precluded development of much-needed therapeutics. Single ISCs give rise to self- renewing/patterning organoids in culture and currently represent the best, non-transformed, physiologic model of the intestinal epithelium. ISCs in the SI exist as multiple populations defined by different proliferative states. Active ISCs (aISC) are highly undifferentiated and continuously divide to renew the intestinal epithelium. In contrast, reserve ISCs are secretory progenitors, express both neuroendocrine hormones and stem cell biomarkers, and divide very slowly. Recently, CRISPR/Cas9 was used to recapitulate sequential in vivo mutations driving CRC in primary human colonic organoids, providing a powerful model for ?omics level analysis and drug screening of human cancer. We hypothesize that secretory progenitor rISCs accumulate driver mutations, which promote transformation to SI-NETs that are supported by the underlying stromal cells. We will test this hypothesis by, (Aim1) adapting ISC organoids and high-throughput culture arrays to determine the genetic and cellular basis of SI-NET initiation, and (Aim 2) mapping the SI-NET cytome using single-cell RNA-seq.